AUTOMATED PNEUMONIA DETECTION USING MACHINE LEARNING ON CHEST X-RAY IMAGES: ENHANCING DIAGNOSTIC ACCURACY AND PATIENT CARE
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https://doi.org/10.48047/Keywords:
.Abstract
Every year, pneumonia affects 7% of the world's population and poses a deadly danger to 4 million individuals. Pneumonia is a respiratory illness brought on by viruses and bacteria inflaming air sacs. Prompt diagnosis is essential, and common signs include cough, shortness of breath, and chest discomfort. However, limited clinical findings and low test sensitivity make it difficult to diagnose pneumonia in youngsters. Chest X-rays are becoming a valuable diagnostic tool, but the traditional method, which involves radiologists manually examining the images, is laborious, subjective, and has variable accuracy.
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References
Ren, Hao, Fengshi Jing, Zhurong Chen, Shan He, Jiandong Zhou, Le Liu, Ran Jing et al. "CheXMed: A multimodal learning algorithm for pneumonia detection in the elderly." Information Sciences 654 (2024): 119854.
Wu, Linghua, Jing Zhang, Yilin Wang, Rong Ding, Yueqin Cao, Guiqin Liu, Changsheng Liufu et al. "Pneumonia detection based on RSNA dataset and anchor-free deep learning detector." Scientific Reports 14, no. 1 (2024): 1-8.
Nalluri, Sravani, and R. Sasikala. "Pneumonia screening on chest X-rays with optimized ensemble model." Expert Systems with Applications 242 (2024): 122705.
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